Geography and Sustainability最新文献

The Regional Climate Model (RegCM) proves valuable for climate analysis and has been applied to a wide range of climate change aspects and other environmental issues at a regional scale. The model also demonstrated success in diverse areas of urban research, including urban heat island studies, extreme climate events analysis, assessing urban resilience, and evaluating urbanization impacts on climate and air quality. Recently, more studies have been conducted in utilizing RegCM to address climate change in cities, due to its enhanced ability over the years to capture meteorological phenomena at city scales. However, there are many challenges associated with its implementation in meso-scale research, which are attributed to various shortcomings and thus create room for further improvement in the model. This paper presents a comprehensive overview of the evolution of the RegCM over the years and its customisation across various parameters, demonstrating its versatility in urban climate studies and underscoring the model’s pivotal role in addressing multifaceted challenges in urban environments. By addressing these aspects, the paper offers valuable insights and recommendations for researchers seeking to enhance the accuracy and efficacy of urban climate simulations using the RegCM system, thereby contributing to the advancement of urban climate science and sustainability.

The amount of impervious surface is increasing rapidly worldwide. Although urban expansion has been studied extensively, the alteration of impervious land cover in rural regions remains under-examined. In particular, insights into the utilization of these sealed surfaces are crucially needed to unravel the underlying dynamics of land use changes beyond urban areas. This study focuses on rural regions from a Swiss case study and presents an analysis of the use of sealed surfaces in such regions, rather than solely quantifying the extent of sealed surfaces. Utilizing a synergistic approach that merges detailed cadastral plans with very-high-resolution remote sensing imagery and sophisticated deep learning algorithms, we characterized the uses of sealed surfaces, including buildings and their surroundings. Our findings reveal that 2.1 % of the study area’s rural regions comprises sealed surfaces - an area comparable to the sealed surfaces in the urban regions. Within these rural regions, transport infrastructure represents 68 % of this impervious surface. Buildings account for 12 %, and their surroundings, constituting 13 %, are utilized primarily for agricultural purposes, including farming and livestock activities. The deep learning approach achieved a classification accuracy of 72 % for a shallow model and 79 % for a deeper model, indicating that mapping building types is possible with reasonable accuracy. The outcomes of this study underscore the critical need to factor in the presence and utilization of impervious land cover within rural regions for the sustainable management of land resources.

Trees provide multiple ecosystem services such as carbon sequestration, hydrological regulation and habitat for arboreal animals. However, they are often removed to support agricultural enterprises. Despite the importance of tree remnants, we know relatively little about how soils differ across sites of varying condition. Here, we describe a study where we examined the relative effects of trees, compared with unvegetated interspaces, on soil functions in remnant patches at sites in good and poor condition in two eucalypt communities in an irrigation area in eastern Australia. We found that, in general, carbon and nutrient cycling were relatively greater beneath trees, and in surface soils, but there were no clear trends in relation to site condition. The values of most soil attributes (e.g., soluble and exchangeable cations, nitrogen, phosphorus) were greater beneath trees, indicating strong fertile island effects in both communities. Overall, our study confirms the importance of trees in remnant patches in agricultural landscapes, particularly those in sites of poor condition. It also suggests that soil processes may still be relatively intact, even in sites in poor condition. Our study reinforces the need to protect trees in remnant woodland reserves to maintain critical ecosystem functions related to nutrient retention. These remnants are important for achieving sustainable management of agricultural systems.

Climate change threatens China’s rice production, making it crucial to assess the impact of climate change and climate year type (CYT) on rice production across regions to safeguard food security. The impact of climate change under nine CYTs with different combinations of temperature and precipitation on two rice cropping systems, including single rice and double rice (early and late rice) was evaluated. The results indicate that: (1) the Northeast region was expected to undergo the greatest warming of 2.03–2.48 °C, and future climate conditions would be dominated by Warm-Humid, Warm-Normal, and Warm-Dry CYTs across all regions. (2) Climate change would significantly shorten anthesis days after sowing and maturity days after sowing of single rice by 6–12 days and 9–24 days, with little change observed for late rice (< 1 day). Late rice yield suffered more from climate change compared to single and early rice yield, declining by 8.8 %–16.13 %. (3) Different CYTs exhibited varying impacts on rice yields. Yields were projected to decrease by approximately 4.765 % to 18.645 % in Warm-Humid, Warm-Normal, and Warm-Dry CYTs. Conversely, the Northeast region was anticipated to experience an increase in yield. (4) Relationships between rice yield and meteorological factors varied by region, variety, and CYT. Among the nine CYTs, high killing degree days, mean daily temperature, mean solar radiation and warm spell duration index were the main factors influencing changes in rice yield, explaining nearly 80 % of yield change. Our results would help to develop adaptation strategies in different regions and rice cropping systems.

The ‘15-minute city’ (15minC) concept, which aspires to bring essential services within reach via a 15-minute walk for all residents, represents a pivotal paradigm shift in sustainable urban development. However, the achievability of this concept for different cities varies considerably across diverse population distributions, urban contexts, and development priorities. In this study, we propose a robust method for evaluating a city’s 15minC potential — a city’s capability to achieve widespread 15-minute accessibility while maintaining an optimal balance between resource efficiency and resident accessibility. We employ the Location Set Covering Problem optimization model to analyze the resources required to achieve full coverage of 15-minute accessibility and the knee point detection algorithm to assess a city’s 15minC potential. Across 23 major Chinese cities, our method exhibits a sharp sensitivity to delineate distinct 15minC potentials. It reveals that cities’ current 15minC development level doesn’t align with their inherent potential uniformly. Key determinants include how well current facility locations match population centers and the population density in remote areas. Further, reducing facility constructions by two-thirds has only a marginal impact on accessibility, emphasizing the need for tailored, data-driven planning in effective and sustainable urban development based on the distinct potentials of cities. Our approach prioritizes resource efficiency, minimizing the inefficient use of facilities that serve only a small portion of residents while maximizing the benefits of the 15minC and therefore has significant implications for a sustainable urban future.

This study aims to develop a system dynamic (SD) forecasting model based on the STIRPAT model to forecast the effect of an IDR 30 per kg CO₂e carbon tax on carbon emissions, estimate future carbon emissions under ten scenarios, without and with the carbon tax, and estimate the environmental Kuznets curve (EKC) to predict Indonesia’s carbon emission peak. Carbon emission drivers in this study are decomposed into several factors, namely energy structure, energy intensity, industrial structure, GDP per capita, population, and fixed-asset investment. This study included nuclear power utilization starting in 2038. The research gaps addressed by this study compared to previous research are (1) use of the ex-ante approach, (2) inclusion of nuclear power plants, (3) testing the EKC hypothesis, and (4) contribution to government policy. The simulation results show that under the carbon tax, carbon emissions can be reduced by improving renewable energy structures, adjusting industrial structures to green businesses, and emphasizing fixed asset investment more environmentally friendly. Moreover, the result approved the EKC hypothesis. It shows an inverse U-shaped curve between GDP per capita and CO₂ emissions in Indonesia. Indonesia’s fastest carbon emission peak is under scenario seven and is expected in 2040. Although an IDR 30 per kg CO₂e carbon tax and nuclear power will take decades to reduce carbon emissions, the carbon tax can still be a reference and has advantages to implement. This result can be a good beginning step for Indonesia, which has yet to gain experience with a carbon tax that can be implemented immediately and is helpful to decision-makers in putting into practice sensible measures to attain Indonesia’s carbon emission peaking. This research provides actionable insights internationally on carbon tax policies, nuclear energy adoption, EKC dynamics, global policy implications, and fostering international cooperation for carbon emission reductions.